View source: R/transform_counts.R
is_paired_end | R Documentation |
Based on two alignment metrics, this function guesses the samples are paired end or not.
is_paired_end(
x,
avg_mapped_read_length = "recount_qc.star.average_mapped_length",
avg_read_length = "recount_seq_qc.avg_len"
)
x |
Either a
RangedSummarizedExperiment-class
created by |
avg_mapped_read_length |
A |
avg_read_length |
A |
A logical()
vector specifying whether each sample was likely
paired-end or not.
Other count transformation functions:
compute_read_counts()
,
compute_scale_factors()
,
transform_counts()
## Download the metadata for SRP009615, a single-end study
SRP009615_meta <- read_metadata(
metadata_files = file_retrieve(
locate_url(
"SRP009615",
"data_sources/sra",
)
)
)
## Are the samples paired end?
is_paired_end(SRP009615_meta)
## Download the metadata for DRP000499, a paired-end study
DRP000499_meta <- read_metadata(
metadata_files = file_retrieve(
locate_url(
"DRP000499",
"data_sources/sra",
)
)
)
is_paired_end(DRP000499_meta)
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